Development of a multi-compartment population balance model for high-shear wet granulation with discrete element method

This paper presents a multi-compartment population balance model for wet granulation coupled with DEM (discrete element method) simulations. Methodologies are developed to extract relevant data from the DEM simulations to inform the population balance model. First, compartmental residence times are...

Full description

Saved in:
Bibliographic Details
Main Authors: Lee, Kok Foong, Dosta, Maksym, McGuire, Andrew D., Mosbach, Sebastian, Wagner, Wolfgang, Heinrich, Stefan, Kraft, Markus
Other Authors: School of Chemical and Biomedical Engineering
Format: Article
Language:English
Published: 2018
Subjects:
Online Access:https://hdl.handle.net/10356/88020
http://hdl.handle.net/10220/44503
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-88020
record_format dspace
spelling sg-ntu-dr.10356-880202023-12-29T06:46:14Z Development of a multi-compartment population balance model for high-shear wet granulation with discrete element method Lee, Kok Foong Dosta, Maksym McGuire, Andrew D. Mosbach, Sebastian Wagner, Wolfgang Heinrich, Stefan Kraft, Markus School of Chemical and Biomedical Engineering Stochastic Weighted Algorithm Granulation This paper presents a multi-compartment population balance model for wet granulation coupled with DEM (discrete element method) simulations. Methodologies are developed to extract relevant data from the DEM simulations to inform the population balance model. First, compartmental residence times are calculated for the population balance model from DEM. Then, a suitable collision kernel is chosen for the population balance model based on particle–particle collision frequencies extracted from DEM. It is found that the population balance model is able to predict the trends exhibited by the experimental size and porosity distributions by utilising the information provided by the DEM simulations. NRF (Natl Research Foundation, S’pore) Accepted version 2018-03-05T06:35:25Z 2019-12-06T16:54:16Z 2018-03-05T06:35:25Z 2019-12-06T16:54:16Z 2017 Journal Article Lee, K. F., Dosta, M., McGuire, A. D., Mosbach, S., Wagner, W., Heinrich, S., et al. (2017). Development of a multi-compartment population balance model for high-shear wet granulation with discrete element method. Computers & Chemical Engineering, 99, 171-184. 0098-1354 https://hdl.handle.net/10356/88020 http://hdl.handle.net/10220/44503 10.1016/j.compchemeng.2017.01.022 en Computers and Chemical Engineering © 2017 Elsevier Ltd. This is the author created version of a work that has been peer reviewed and accepted for publication by Computers and Chemical Engineering, Elsevier Ltd. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1016/j.compchemeng.2017.01.022]. 54 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Stochastic Weighted Algorithm
Granulation
spellingShingle Stochastic Weighted Algorithm
Granulation
Lee, Kok Foong
Dosta, Maksym
McGuire, Andrew D.
Mosbach, Sebastian
Wagner, Wolfgang
Heinrich, Stefan
Kraft, Markus
Development of a multi-compartment population balance model for high-shear wet granulation with discrete element method
description This paper presents a multi-compartment population balance model for wet granulation coupled with DEM (discrete element method) simulations. Methodologies are developed to extract relevant data from the DEM simulations to inform the population balance model. First, compartmental residence times are calculated for the population balance model from DEM. Then, a suitable collision kernel is chosen for the population balance model based on particle–particle collision frequencies extracted from DEM. It is found that the population balance model is able to predict the trends exhibited by the experimental size and porosity distributions by utilising the information provided by the DEM simulations.
author2 School of Chemical and Biomedical Engineering
author_facet School of Chemical and Biomedical Engineering
Lee, Kok Foong
Dosta, Maksym
McGuire, Andrew D.
Mosbach, Sebastian
Wagner, Wolfgang
Heinrich, Stefan
Kraft, Markus
format Article
author Lee, Kok Foong
Dosta, Maksym
McGuire, Andrew D.
Mosbach, Sebastian
Wagner, Wolfgang
Heinrich, Stefan
Kraft, Markus
author_sort Lee, Kok Foong
title Development of a multi-compartment population balance model for high-shear wet granulation with discrete element method
title_short Development of a multi-compartment population balance model for high-shear wet granulation with discrete element method
title_full Development of a multi-compartment population balance model for high-shear wet granulation with discrete element method
title_fullStr Development of a multi-compartment population balance model for high-shear wet granulation with discrete element method
title_full_unstemmed Development of a multi-compartment population balance model for high-shear wet granulation with discrete element method
title_sort development of a multi-compartment population balance model for high-shear wet granulation with discrete element method
publishDate 2018
url https://hdl.handle.net/10356/88020
http://hdl.handle.net/10220/44503
_version_ 1787136469405532160